Energy management means to optimize one of the most complex and important technical creations that we know: the energy system. While there is plenty of experience in optimizing energy generation and distribution, it is the demand side that receives increasing attention by research and industry. Demand Side Management (DSM) is a portfolio of measures to improve the energy system at the side of consumption. It ranges from improving energy efficiency by using better materials, over smart energy tariffs with incentives for certain consumption patterns, up to sophisticated real-time control of distributed energy resources. This paper gives an overview and a taxonomy for DSM, analyzes the various types of DSM, and gives an outlook on the latest demonstration projects in this domain.

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Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads

The enabling of ac microgrids in distribution networks allows delivering distributed power and providing grid support services during regular operation of the grid, as well as powering isolated islands in case of faults and contingencies, thus increasing the performance and reliability of the electrical system. The high penetration of distributed generators, linked to the grid through highly controllable power processors based on power electronics, together with the incorporation of electrical energy storage systems, communication technologies, and controllable loads, opens new horizons to the effective expansion of microgrid applications integrated into electrical power systems. This paper carries out an overview about microgrid structures and control techniques at different hierarchical levels. At the power converter level, a detailed analysis of the main operation modes and control structures for power converters belonging to microgrids is carried out, focusing mainly on grid-forming, grid-feeding, and grid-supporting configurations. This analysis is extended as well toward the hierarchical control scheme of microgrids, which, based on the primary, secondary, and tertiary control layer division, is devoted to minimize the operation cost, coordinating support services, meanwhile maximizing the reliability and the controllability of microgrids. Finally, the main grid services that microgrids can offer to the main network, as well as the future trends in the development of their operation and control for the next future, are presented and discussed.

Control of Power Converters in AC Microgrids

The analysis of the small-signal stability of conventional power systems is well established, but for inverter based microgrids there is a need to establish how circuit and control features give rise to particular oscillatory modes and which of these have poor damping. This paper develops the modeling and analysis of autonomous operation of inverter-based microgrids. Each sub-module is modeled in state-space form and all are combined together on a common reference frame. The model captures the detail of the control loops of the inverter but not the switching action. Some inverter modes are found at relatively high frequency and so a full dynamic model of the network (rather than an algebraic impedance model) is used. The complete model is linearized around an operating point and the resulting system matrix is used to derive the eigenvalues. The eigenvalues (termed "modes") indicate the frequency and damping of oscillatory components in the transient response. A sensitivity analysis is also presented which helps identifying the origin of each of the modes and identify possible feedback signals for design of controllers to improve the system stability. With experience it is possible to simplify the model (reduce the order) if particular modes are not of interest as is the case with synchronous machine models. Experimental results from a microgrid of three 10-kW inverters are used to verify the results obtained from the model

Modeling, Analysis and Testing of Autonomous Operation of an Inverter-Based Microgrid

The increasing interest in integrating intermittent renewable energy sources into microgrids presents major challenges from the viewpoints of reliable operation and control. In this paper, the major issues and challenges in microgrid control are discussed, and a review of state-of-the-art control strategies and trends is presented; a general overview of the main control principles (e.g., droop control, model predictive control, multi-agent systems) is also included. The paper classifies microgrid control strategies into three levels: primary, secondary, and tertiary, where primary and secondary levels are associated with the operation of the microgrid itself, and tertiary level pertains to the coordinated operation of the microgrid and the host grid. Each control level is discussed in detail in view of the relevant existing technical literature.

Trends in Microgrid Control

In this paper, the idea of operating an inverter to mimic a synchronous generator (SG) is motivated and developed. We call the inverters that are operated in this way synchronverters. Using synchronverters, the well-established theory/algorithms used to control SGs can still be used in power systems where a significant proportion of the generating capacity is inverter-based. We describe the dynamics, implementation, and operation of synchronverters. The real and reactive power delivered by synchronverters connected in parallel and operated as generators can be automatically shared using the well-known frequency- and voltage-drooping mechanisms. Synchronverters can be easily operated also in island mode, and hence, they provide an ideal solution for microgrids or smart grids. Both simulation and experimental results are given to verify the idea.

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Synchronverters: Inverters That Mimic Synchronous Generators

This paper presents an energy management system (EMS) for a stand-alone droop-controlled microgrid, which adjusts generators output power to minimize fuel consumption and also ensures stable operation. It has previously been shown that frequency-droop gains have a significant effect on stability in such microgrids. Relationship between these parameters and stability margins are therefore identified, using qualitative analysis and small-signal techniques. This allows them to be selected to ensure stability. Optimized generator outputs are then implemented in real-time by the EMS, through adjustments to droop characteristics within this constraint. Experimental results from a laboratory-sized microgrid confirm the EMS function.

https://spiral.imperial.ac.uk:8443/bitstream/10044/1/15430/2/IEEE%20Transactions%20on%20Power%20Electronics_23_5_2008.pdf

Energy Management in Autonomous Microgrid Using Stability-Constrained Droop Control of Inverters

Rectifiers and voltage regulators acting as constant power loads form an important part of a microgrid’s total load. In simplified form, they present a negative incremental resistance and beyond that, they have control loop dynamics in a similar frequency range to the inverters that may supply a microgrid. Either of these features may lead to a degradation of small-signal damping. It is known that droop control constants need to be chosen with regard to damping, even with simple impedance loads. Actively controlled rectifiers have been modeled in nonlinear state-space form, linearized around an operating point, and joined to network and inverter models. Participation analysis of the eigenvalues of the combined system identified that the low-frequency modes are associated with the voltage controller of the active rectifier and the droop controllers of the inverters. The analysis also reveals that when the active load dc voltage controller is designed with large gains, the voltage controller of the inverter becomes unstable. This dependence has been verified by observing the response of an experimental microgrid to step changes in power demand. Achieving a well-damped response with a conservative stability margin does not compromise normal active rectifier design, but notice should be taken of the inverter–rectifier interaction identified.

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Dynamic Stability of a Microgrid With an Active Load

Control of inverter-based micro-grids

Inverters are a necessary interface for several forms of distributed generation (DG) and where they form a microgrid they have the potential to offer high power quality. The challenge is to coordinate the actions of a group of inverters so that they offer the level of power quality known to be possible from fast local control of a single inverter. The case examined here is a power park of several inverter-based DG in relatively close proximity. A basic requirement is that the inverters regulate the grid voltage and share the real and reactive power demands according to their ratings. In small girds with high proportions of nonlinear and unbalanced loads it is also important to actively control the waveform quality in terms of harmonics, transient disturbances, and balance. Further, it is important that these duties are shared equally between the units rather than having one master unit taking the lead in the voltage control function. A constraint faced in designing a sharing system is the limited bandwidth of signal communication even over distances of a few meters. A control method is proposed that separates the control tasks in the frequency domain. Power sharing and voltage regulation are controlled centrally and commands are distributed through a low-bandwidth communication link. Waveform quality functions are controlled in high bandwidth controllers distributed to each local inverter. Experimental tests on a grid of three 10-kVA inverters are used to show that the method fully exploits the inherent fast response of the inverters while also ensuring voltage balance even with extreme load imbalance. It is shown that circulating currents are avoided during steady state and transients

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Milan Prodanovic

Papers

Modeling, Analysis and Testing of Autonomous Operation of an Inverter-Based Microgrid

Energy Management in Autonomous Microgrid Using Stability-Constrained Droop Control of Inverters

Dynamic Stability of a Microgrid With an Active Load

Control of inverter-based micro-grids

High-Quality Power Generation Through Distributed Control of a Power Park Microgrid